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Chronicles

The story behind the story

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Substack partners with AI-detection tool Pangram, allowing users to scan text longer than 100 words for an estimate of how much was written with AI assistance

Building trust in the AI age  —  It's getting harder to tell what's real on the internet.  —  This is less true on Substack, and we aim to keep it that way.

The Substack Post Chris Best

Context & Ripple Effects

Substack’s move follows Pangram’s finding that roughly a quarter of long-form social posts in its sample were fully AI-generated, making provenance a more salient platform concern as AI-written material spreads. Pangram’s social-content analysis gives the partnership a concrete demand backdrop.

The platform has previously added creator-production features, including AI-made transcript tools for video creators. The new integration shifts attention from helping creators make content to helping readers and publishers assess how it was made.

First-order effects

  • Substack users can now run qualifying text through Pangram for an estimate of AI assistance, adding a visible verification option to the publishing platform.
  • Pangram gains distribution inside a creator platform, while Substack positions trust assessment as part of its product experience rather than leaving it to external tools.

Second-order effects

  • Creators and publishers may face greater reader scrutiny of authorship claims, even though a detector’s output is an estimate rather than proof.
  • Other publishing and social platforms face added pressure to offer provenance or detection features; however, scale also raises the practical cost of disputed flags, a concern highlighted in warnings about detector false positives at scale.

Third-order effects

  • If such tools become routine, content platforms may increasingly treat AI-use assessment as trust infrastructure alongside moderation and publishing controls.
  • The durable challenge will be governance around detector results: platforms will need to distinguish an AI-use signal from a definitive authorship judgment to avoid turning probabilistic scores into automated reputational penalties.

The trend: This is part of the shift from generative-AI creation features toward operational systems for assessing and communicating content provenance.

Discussion

  • @emollick Ethan Mollick on x
    This is an interesting experiment (and I am glad that I have always written my own posts!)
  • @thezvi Zvi Mowshowitz on x
    Great stuff, with the full Pangram. Fun and if possible I will be turning this on by default. Will only work on text posted going forward - your past AI usage is safe.
  • @perrymetzger Perry E. Metzger on x
    Any oracle for “written by an AI” can be used to fine tune an AI to evade the detector. There is no point to such detectors, they cannot work for long, certainly not as commercial products.
  • @emily_sundberg Emily Sundberg on x
    Substack will now be able to tell readers if your newsletter was written by Claude https://substack.com/... [image]
  • @substack @substack on x
    We're also introducing tools for creators, including the ability to run Pangram on your drafts prior to publication, and to add a “How I make this” statement where you explain your process and set expectations for readers.
  • @substack @substack on x
    Today, Substack is launching an AI detection feature, via an integration with @pangram. Going forward, you'll be able to scan posts, replies, and comments on the Substack app to see an estimate of how much of it was written by a human, or with AI assistance. [image]
  • @informor Mor Naaman on bluesky
    Why AI detection is a losing battle for everyone.  If readers use it, writers will use it too (and their AI can even help them avoid it).  [embedded post]
  • @caseynewton Casey Newton on bluesky
    I have to say ... I think this is great [embedded post]
  • r/slatestarcodex r on reddit
    Substack partners with Pangram to offer one-click AI detection on any article or comment
  • @signulll @signulll on x
    it'd be absolutely hilarious if linkedin actually implemented this.